AI Agent Developer

AI Agent Developer (LLM Specialist) Role Overview

The AI Agent Developer is responsible for designing, building, and deploying intelligent autonomous or semi-autonomous agents powered by Large Language Models (LLMs). This role focuses on enabling complex workflows, reasoning capabilities, system integration, and secure data interaction across enterprise environments.

• Architect and implement AI-powered agents using LLMs (e.g., GPT, Claude, Llama, Mistral, Gemini).
• Develop prompt workflows, retrieval-augmented generation (RAG), and multi-step reasoning.
• Configure agent behaviors for decision‑making, task execution, and contextual understanding.
• Implement function calling, tool use, or API integration to extend agent capabilities.

• Connect agents to internal systems, databases, knowledge bases, and APIs.
• Use frameworks such as Lang Chain, Llama Index, Haystack, Semantic Kernel, or custom pipelines.
• Implement connectors for CRMs, ERPs, ticketing platforms, or document repositories.

• Create structured and unstructured knowledge retrieval mechanisms.
• Build and manage vector databases (Pinecone, Weaviate, Chroma, Milvus, Azure AI Search).
• Implement embeddings, chunking strategies, metadata tagging, and query optimization.

• Design agent orchestration pipelines to handle multi-agent collaboration.
• Enable agents to automate research, reporting, email drafting, document processing, and customer interactions.
• Integrate with workflow tools like Zapier, Airflow, UiPath, or Power Automate.

• Fine‑tune or customize LLMs using organization‑specific data.
• Evaluate model performance for accuracy, latency, cost, hallucinations, and compliance.
• Apply guardrails, prompt validation, and reinforcement techniques.

• Enforce data privacy and governance standards (GDPR, HIPAA, SOC2, ISO, CCPA).
• Implement role‑based access and secure API token handling.
• Apply content filtering, moderation, and usage monitoring.

• Work with cross‑functional teams (engineering, design, product, legal, security).
• Maintain technical documentation, agent configuration logs, and deployment playbooks.
• Train internal teams on capabilities and responsible use.

• Experience with Python, Type Script/JavaScript, or Go.
• Familiarity with API development (REST, Graph
  
  QL, JSON).
• Experience with cloud platforms:
  Azure OpenAI, AWS Bedrock, GCP Vertex AI, or Hugging Face.
• Knowledge of vector databases and retrieval architectures.

• Strong understanding of LLM architectures, embeddings, prompt engineering, and RAG.
• Experience with fine‑tuning or model adaptation techniques.
• Familiarity with agent frameworks (Lang Chain Agents, CrewAI, Auto Gen, Semantic Kernel).

• Experience building chatbots, copilots, or domain‑specific assistants.
• Knowledge of event‑driven architecture, microservices, or serverless functions.
• Exposure to MLOps or LLMOps tooling.

We are an equal opportunity employer and committed to a diverse workforce.